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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
351

Statistical mechanical studies of autoassociative and feedforward neural networks

O'Kane, Dominic January 1993 (has links)
No description available.
352

Computer vision as an aid for the visually impaired

Molton, Nicholas David January 1998 (has links)
No description available.
353

Mechanics of the ligament deficient knee

Imran, Ahmed January 1998 (has links)
No description available.
354

Optimisation in neural networks

Wendemuth, Andreas January 1994 (has links)
No description available.
355

Statistical mechanics of neural networks

Rau, Albrecht January 1992 (has links)
No description available.
356

Multi-layer neural networks and their implementation in analogue VLSI

Tombs, Jonathan Noel January 1992 (has links)
No description available.
357

Applications of neural networks to control systems

Ruano, Antonio Eduardo de Barras January 1992 (has links)
No description available.
358

Laterality differences in memory and attention

Hogan, Kevin M. January 1981 (has links)
A critical review of the auditory selective attention literature is presented, particular reference is made to methodological issues arising from the asymmetrical hemispheric representation of language in the context of the dominant research technique dichotic shadowing. Subsequently the concept of cerebral localization is introduced, and the experimental literature with reference to models of laterality effects in speech and audition discussed. The review indicated the importance of hemispheric asymmetries insofar as they might influence the results of dichotic shadowing tasks. It is suggested that there is a potential overlap between models of selective attention and hemispheric differences. In Experiment I, ~ a key experiment in auditory selective attention is replicated and by exercising control over possible laterality effects some of the conflicting results of earlier studies were reconciled. The three subsequent experiments, II, III and IV, are concerned with the recall of verbally shadowed inputs. A highly significant and consistent effect of ear of arrival upon the serial position of items recalled is reported. Experiment V is directed towards an analysis of the effect that the processing of unattended inputs has upon the serial position of attended items that are recalled. A significant effect of the type of unattended material upon the recall of attended items was found to be influenced by the ear of arrival of inputs. In Experiment VI, differences between the two ears as attended and unattended input channels were clarified. Two main conclusions were drawn from this work. First, that the dichotic shadowing technique cannot control attention. Instead the task aprocessing both channels of dichotic inputs is unevenly shared bet\'reen the hemispheres as a function of the ear shadowed. Consequently, evidence for the processing of unattended information is considered in terms of constraints imposed by asymmetries in the functional organization of language, not in terms of a limited processing capacity model. The second conclusion to be drawn is that laterality differences can be effectively examined using the dichotic shadowing technique, a new model of laterality differences is proposed and discussed.
359

Investigation of a generalised version of Amari's continuous model for neural networks

Roque, Antonio Carlos January 1992 (has links)
No description available.
360

Reinforcement learning in intelligent control : a biologically-inspired approach to the relearning problem

D'Cruz, Brendan January 1998 (has links)
The increasingly complex demands placed on control systems have resulted in a need for intelligent control, an approach that attempts to meet these demands by emulating the capabilities found in biological systems. The need to exploit existing knowledge is a desirable feature of any intelligent control system, and this leads to the relearning problem. The problem arises when a control system is required to effectively learn new knowledge whilst exploiting still useful knowledge from past experiences. This thesis describes the adaptive critic system using reinforcement learning, a computational framework that can effectively address many of the demands in intelligent control, but is less effective when it comes to addressing the relearning problem. The thesis argues that biological mechanisms of reinforcement learning (and relearning) may provide inspiration for developing artificial intelligent control mechanisms that can better address the relearning problem. A conceptual model of biological reinforcement learning and relearning is presented, and the thesis shows how inspiration derived from this model can be used to modify the adaptive critic. The performance of the modified adaptive critic system on the relearning problem is investigated based on simulations of the pole balancing problem, and this is compared to the performance of the original adaptive critic system. The thesis presents an analysis of the results from these simulations, and discusses the significance of these results in terms of addressing the relearning problem.

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